Chaaraoui, Alexandros Andre, Padilla-Lopez, Jose Ramon and Florez-Revuelta, Francisco (2013) Fusion of skeletal and silhouette-based features for human action recognition with RGB-D devices. In: 2013 IEEE International Conference on Computer Vision Workshops; 2 - 8 Dec 2013, Sydney, Australia.

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Official URL:	http://dx.doi.org/10.1109/ICCVW.2013.19
Item Type:	Conference or Workshop Item (Paper)
Event Title:	2013 IEEE International Conference on Computer Vision Workshops
Organising Body:	Institute of Electrical and Electronics Engineers
Additional Information:	This work was supported by the European Commission [PIEF-GA-2010- 274649]; Spanish Ministry of Science and Innovation [TIN2010-20510-C04-02]; and the Conselleria d’Educacio, Formacio i Ocupacio of the Generalitat Valenciana [ACIF/2011/160, ACIF/2012/064].
Uncontrolled Keywords:	feature extraction, image colour analysis, image fusion, image sensors, learning (artificial intelligence), pose estimation, 2D shape, 3D skeletal pose information, MSR Action3D dataset, Microsoft Kinect, RGB-D devices, characteristic value, feature extraction techniques, feature fusion, human action recognition, human gestures, learning method, marker-less body pose estimation, recognition rates, red-green-blue-depth device, silhouette-based features, skeletal features, viewpoint, estimation, feature extraction, joints, real-time systems, shape, three-dimensional displays
Research Area:	Research Areas > Computer science and informatics
Faculty, School or Research Centre:	Faculty of Science, Engineering and Computing (until 2017) > School of Computing and Information Systems
Date Deposited:	24 Jul 2014 07:57
Last Modified:	20 Jun 2022 16:38
DOI:	https://doi.org/10.1109/ICCVW.2013.19
URI:	https://eprints.kingston.ac.uk/id/eprint/28662

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